*** One-Child Policy, Marriage Distortion, and Welfare Loss ***
*** by Wei Huang, Yinghao Pan and Yi Zhou ***

clear all 
set more off
set scheme s1color
cap log close 
graph set window fontface "Times New Roman"

set niceness 10
gl MAIN = "F:\Dropbox"

gl path1 = "$MAIN/Census"
gl path2 = "$MAIN/Marriage/Working_data"
gl path3 = "$MAIN/Marriage/Restat/dataverse_files/Results" 
gl path4 = "$MAIN/Marriage/Restat/dataverse_files/Graphics" 
gl CONTROL = " year_birth sex#age urban_hk prov_hk##c.(year_birth ) "

***** Appendix Table A18 *****

use "$path2/unmarried", clear
keep if relation == 0 | relation == 1 | relation == 2 | relation == 6 

merge 1:1 wave area hhid name relation using "$path2/min_marr_policy", keepusing(marry_1 marry_2 marry_3)


drop if mi(hktype)
replace urban = hktype == 1 
su age 

cap gen female = 1-male
cap gen han = 1- minority 

replace unmarried = unmarried * 100 
gen unmarr_25 = marr_age > 25 if !mi(marr_age)
replace unmarr_25 = 1 if unmarried == 100 
replace unmarr_25 = unmarr_25 *100 

gen urban_hk = hktype == 2 

egen clsid = group(prov_hk year_birth)

gen marry_9 = unmarried == 0 & (mi(marry_1) & mi(marry_2) & mi( marry_3))

recode marry_1 marry_2 marry_3 (. = 0) 

gen HH = marry_1 * 100 
gen HM = marry_2 * 100 
gen MM = marry_3 * 100 
gen Other = marry_9 * 100 
gen HOMO = HH + MM
su HOMO

keep if age <= 55 
keep if age > 25
keep if year_birth <= 1980 
keep if Other == 0 
keep if year_birth != 1959 & year_birth != 1960 & year_birth !=1961

egen fine_16_20 = rowmean(fine_16 fine_17 fine_18 fine_19 fine_20)

cap erase "$path3/marriage_femine.xls"
cap erase "$path3/marriage_femine.txt"

gl CONTROL = " year_birth sex#age urban_hk prov_hk##c.(year_birth ) "

foreach sample in "1" {
foreach gender in "1" { 
foreach y_var in   "unmarried"   {
foreach policy in "1" "mino_policy == 1"  "mino_policy == 0"  {
foreach eth in  "han" "han == 0"{
foreach age in "16_25"  {
preserve 
keep if `sample' & `policy' & `gender' & `eth'

reghdfe `y_var' fine_`age' [aw = aw], a($CONTROL)  cluster(prov_hk)
su `y_var' [aw = aw]
outreg2 using "$path3/marriage_femine.xls", append bracket addstat(Y, `r(mean)') ctit(`sample' &`y_var' & `policy' & `gender' & `eth') keep(fine_`age')  dec(3)

restore


}
}
}
}
}
}



foreach sample in  "unmarried == 0"{
foreach gender in "1" { 
foreach y_var in   "HM"  {
foreach policy in "1" "mino_policy == 1"  "mino_policy == 0"  {
foreach eth in  "han" "han == 0"{
foreach age in "16_25"  {
preserve 
keep if `sample' & `policy' & `gender' & `eth'

reghdfe `y_var' fine_`age' [aw = aw], a($CONTROL)  cluster(prov_hk)
su `y_var' [aw = aw]
outreg2 using "$path3/marriage_femine.xls", append bracket addstat(Y, `r(mean)') ctit(`sample' &`y_var' & `policy' & `gender' & `eth') keep(fine_`age')  dec(3)

restore


}
}
}
}
}
}


keep if sex == 2 // women 

egen n_birth = rowtotal(numbirm numbirf)
replace n_birth = . if age > 45

gl CONTROL = " year_birth sex#age urban_hk prov_hk##c.(year_birth ) "

foreach sample in  "n_birth != ."{
foreach gender in "sex == 2" {
foreach y_var in "n_birth"  {
foreach policy in "1" "mino_policy == 1"  "mino_policy == 0"  {
foreach eth in  "han" "han == 0"{
foreach age in "16_25" {
preserve 
keep if `sample' & `policy' & `gender' & `eth'


reghdfe `y_var' fine_`age'  [aw = aw], a($CONTROL)  cluster(prov_hk)
su `y_var' [aw = aw]
outreg2 using "$path3/marriage_femine.xls", append bracket addstat(Y, `r(mean)') ///
 ctit(`sample' &`y_var' & `policy' & `gender' & `eth') keep(fine_`age')  dec(3)


restore


}
}
}
}
}
}
